Systems and Methods for Planning and Executing an Advertising Campaign Targeting TV Viewers and Digital Media Viewers Across Formats and Screen Types

ABSTRACT

Systems and methods are disclosed for analyzing a fused sample of viewership data to determine a behavior profile of online viewers who watched and/or didn&#39;t watch certain TV advertisements, where the TV advertisements are aligned with campaign targeting characteristics desired by an advertiser/client working with a demand side platform. Then, a campaign targeting plan is developed for dividing an advertising budget between digital media and TV impressions. The digital media portion of the campaign profiles Media Properties (MPs) contained in a historical database from past digital advertising campaigns across multiple digital formats and screens, and aligns digital ad placement with MPs having desired targeting characteristics. An optimized apportionment is automatically produced between TV and digital media spending based on an advertiser/client&#39;s goals of duplicating or not duplicating viewership of an advertisement between TV and digital media, or alternately based on cost alone. Alternately, the apportionment can be guided interactively.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 62/069,213 filed Oct. 27, 2014.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to systems and methods forplanning and managing advertising campaigns that include both digitalmedia advertising and TV advertising across one or more digital formatsand screens.

2. Prior Art

In the RTB (Real-Time Bidding) environment for electronic mediaimpression auctions, an electronic advertising agency/consolidatoroperating a demand-side platform receives billions of daily auctionopportunities for electronic media impressions from partners likeGoogle®, Yahoo®, etc. These partners operate auctions for ad impressionsand then place electronic ads based on auction results. A partner'sauction is considered an external auction with respect to a demand-sideplatform where an internal auction may also be operated to determinewhich advertisements, also referred to herein as ads, and bids aresubmitted to the external auction. Each ad impression opportunityincludes information parameters about the ad impression—for example, thetarget website, geolocation of the user, ad size, user cookie, etc, thatare used for targeting purposes. The demand side platform then processeshundreds of ads in their system, supplied by advertiser clients alongwith desired filtering/targeting parameters, against informationparameters supplied by the partner, and filters out any ads that do notqualify (for example the ad does not want to target Youtube.com®). Forads that are not removed due to a mismatch with targeting parameters,the demand-side platform then evaluates the corresponding bids thatrepresent how much each client advertiser is willing to pay. The winningbid in the internal auction is then sent to the external auction tocompete for the impression opportunity.

Note that in some scenarios, the electronic advertisingagency/consolidator operating a demand-side platform and theadvertiser/client may in fact be the same entity—for instance when theycomprise a large organization with an internal advertising departmentcapable of acting as a demand-side platform. Also, in such an instance,there may be no internal auction—just a submission to an externalauction.

With the ever increasing growth of digital advertising,advertiser/clients are dealing with splitting their ad budget between TVand digital media. Digital media includes any electronic media formatother than TV—essentially all digital formats that can be planned anddelivered electronically. Digital media locations where an ad may beplaced are called Media Properties. A Media Property or MP as describedherein represents a specific instance of a media platform forelectronically delivering information to a viewer. An MP as referencedherein usually refers to a website or URL on the Internet, however mayalso refer for example and without limitation to an App ID, a Game ID,or other digital electronic media including for example electronicbillboards—small and large. Even digital watches with wirelessconnectivity are a form of MP.

As used in describing the invention as defined herein, television or TVincludes:

Connected TV;

VOD (Video on Demand);

Broadcast TV;

Cable TV; and

TV programming provided online.

VOD is further defined as systems that allow users to select andwatch/listen to video or audio content when they choose to, rather thanhaving to watch at a specific broadcast time. IPTV technology is oftenused to bring video on demand to televisions and personal computers.Television VOD systems can either stream content through a set-top box,a computer or other device, allowing viewing in real time, or downloadit to a device such as a computer, digital video recorder (also called apersonal video recorder) or portable media player for viewing at anytime.

Television programming in general may be therefore viewed onconventional TV sets, or on any digital media viewing device, includingwithout limitation PC/laptops, tablets, smartphones, and even digitalwatches. A viewer may be either a person, cookie, household, or anygroup of persons that watch the same programming—regardless of whetheror not they watch simultaneously.

Current tools for helping advertisers split their budget between TV anddigital media only deal with MP categorizations in aggregate, andtypically only with respect to demographic characteristics such as ageand gender. Methods are needed to more precisely plan and predict crossformat ad campaigns where both TV and digital media are targeted in thesame campaign. In particular, it would be useful to plan a campaign suchthat viewers who did not watch certain TV ads get to see them on digitalmedia. It would also be useful at times to reinforce the viewing ofcertain TV ads by targeting the same viewers on digital media in orderto increase the frequency of viewership of those ads.

Specific problems faced by a planner at an advertiser/client may include(written from the perspective of the planner):

-   -   Roughly how much incremental reach can I get by spending a        portion of my TV budget on online video?    -   How do I get a controlled amount of additional frequency of        impressions against targets that have likely seen my ads on TV?    -   Exactly how much should I spend on online video ads based on        various goals: budget, frequency, reach, viewable?    -   How can I execute the digital and television portions of the        campaign as easily as possible on an electronic platform, where        planning and execution are integrated?    -   Exactly how much of the next campaign's share of budget should I        spend on video?    -   How much should I spend on VOD and other avenues that provide        incremental reach? How can I execute and track my ad spend        across all formats easily?

More specifically, a planner may have the following needs and goals(written from the perspective of the planner):

-   -   1. As a Planner, I need the latest data to be included in the TV        Planning tool so that I can be confident in the results of the        tool, by recognizing that the data from my historical TV buy is        correct.    -   2. As a Planner, I need to have access to the correct and        up-to-date data from the demand-side platform so that I can        compare costs and reach versus my TV buy data historically.    -   3. As a Planner, I need to view the impact of shifting away some        of my historical TV budget to online video advertising (executed        via a demand-side platform) so that I can assess the impact of        this shift on the unduplicated reach gains I can achieve.    -   4. As a Planner, I need to be able to easily execute a campaign        with a demand-side platform for the online video ad portion        based on the hypothetical TV and OLV (digital media) spend that        I create in the planner, so that I can save time and reap the        benefits around transparency and delivery that the demand-side        platform offers.    -   5. As a Planner, I need to be able to apply a discount to the        ‘rack rates’ that are quoted as ‘spend’ in the Nielsen TV data        so that discounts I received from networks are included in the        analysis, making my hypothetical spend plan more realistic.    -   6. As a Planner, I need to be able to ‘save’ a draft spending        plan that I can access later so that I don't have to set up the        analysis again after I've considered the plan over some time.    -   7. Preferably, the planning tool must be available via a        public-facing website so I can easily perform prototype plans.    -   8. As a Planner, I need to be able to have the planning tool        figure out the optimal amount of online video ad spend based on        at least three different types of goals given the overall        historical TV budget: maximize unduplicated reach at the same        budget, maximize frequency at the same budget, and the most        cost-effective reach across all available digital and TV formats        and screens, so that I can tune my spend optimization to my        particular marketing goal.

DEFINITIONS

-   -   Planner—a user of the invention including one who operates/uses        the user interface. A planner may belong to a DSP organization        or to an advertiser/client organization.    -   Media avails or “avails”: Unsold units of time available for        broadcasters to sell to advertisers. The number of impressions        available for purchase on a daily or monthly basis for a given        media property.    -   TV Base Plan: A TV advertising campaign that has already been        run and where historical viewer information is available    -   OT CPM: Cost-per-Impression (per 1,000 impressions) for        on-target impressions    -   Incremental reach: Viewers reached (by the invention) that were        not reached by the TV Base Plan    -   PTV—“Programmatic TV”    -   CPM—cost per 1,000 impressions    -   CPP—cost per (GRP) point    -   eCPM—ad revenue generated per 1,000 impressions    -   eCPP—ad revenue generated per (GRP) point    -   VOD—Video on Demand    -   OLV—Online Video    -   MVPD (Multichannel Video Programming Distributor)    -   Xscreen or Cross-Screen—Campaigns that target multiple diverse        screens: TV; Desktop; tablet; smartphone; etc.    -   HH—Household    -   Demo and Demo Targeting—Demographic Segment (Age and Gender)    -   Strategic Targeting—Targeting other than Demographic. Strategic        targeting can include without limitation and for example any or        all of: buying behavior; income; ethnicity; education; children;        home; auto; and pets.    -   Media Property or just “Property”—Any screen type where an        advertisement may appear    -   Daypart—Portions of a day where media may be viewed    -   Demand-Side Platform (DSP) An organization that performs an        advertising agency function for advertisers/clients to plan and        operate advertising campaigns on their behalf. A DSP (such as        TubeMogul, Inc.) may develop and operate a proprietary system        for planning and executing advertising campaigns, including        profiling Viewers and Media Properties. Such as DSP operated        system is also a source of data from previous advertising        campaigns. Note that a DSP may represent client companies, or        alternately be captive to a company or operate as a department        within a company.    -   Fusion—A source of 3^(rd) party data (e.g., Nielsen) that merges        multiple and diverse datasets of viewership information into a        single database.    -   NPN—A source of 3^(rd) party data such as Nielsen's “National        People Meter”    -   SSP—Supply Side Partner    -   DSP—Demand Side Platform    -   Sites—Websites    -   DT—Desktop    -   Linear TV—Conventional time-and-channel-based TV    -   KPI—Key Performance Indicator    -   Comscore—a 3^(rd) party provider of data regarding advertising        campaigns    -   Nielsen—a 3^(rd) party provider of viewership data and related        tools

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an overview block diagram describing system components anddata flow for a demand side platform according to the invention, with afocus on planning and executing a future cross format campaign.

FIG. 2 shows a flow chart describing a process for planning a crossformat campaign with emphasis on reaching unexposed TV viewers.

FIG. 3 shows a flow chart describing a process for planning a crossformat campaign with emphasis on reinforcing viewership.

FIG. 4 shows a flow chart describing a process for planning a crossformat campaign with emphasis on achieving the lowest cost perimpression.

FIG. 5 shows a matrix defining different data sets used for cross formatadvertising campaign planning.

FIG. 6 shows how the various data sets of FIG. 5 are linked and analyzedin creating a cross format advertising campaign.

FIG. 7 shows one exemplary user interface for the planning stage of across format campaign.

FIG. 8 shows an exemplary user interface for the planning stage of across format campaign where a planner may observe the effect of shiftingportions of their TV advertising budget to digital media.

FIG. 9 shows an alternative functionality for guiding the split betweenTV ad spending and digital media ad spending.

FIG. 10 shows the user interface for a planning tool according to theinvention which allows planners to adjust their campaign and observeprojected results in terms of on-target impressions, GRPs, and cost.

FIG. 11 shows a planning tool for a cross format platform focused on GRPor CPM results and including advanced (strategic) targeting choices.

FIG. 12 shows an additional planning tool for a cross format campaignincluding a graph indicating incremental reach.

FIG. 13 shows an additional planning tool for a cross format campaignwhere results are shown in terms of CPP (cost per GRP point) and costfor on target impressions.

FIG. 14 shows an additional planning tool for cross format campaignincluding target placements for both TV and digital media.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Systems and methods are disclosed for analyzing a fused sample ofviewership data to determine a behavior profile of online viewers whowatched and/or didn't watch certain TV advertisements, where the TVadvertisements are aligned with campaign targeting characteristicsdesired by an advertiser/client working with a demand side platform.Then, a campaign targeting plan is developed for dividing an advertisingbudget between digital media and TV impressions. The digital mediaportion of the campaign profiles Media Properties (MPs) contained in ahistorical database from past digital advertising campaigns acrossmultiple digital formats and screens, and aligns digital ad placementwith MPs having desired targeting characteristics. An optimizedapportionment is automatically produced between TV and digital mediaspending based on an advertiser/client's goals of duplicating or notduplicating viewership of an advertisement between TV and digital media,or alternately based on cost alone. Alternately, the apportionment canbe guided interactively.

FIG. 1 shows an overview block diagram describing system components anddata flow for a demand side platform according to the invention, with afocus on planning and executing a future cross format campaign based on3^(rd) party TV and digital viewership information combined withhistorical digital media viewership information compiled over pastcampaigns by the demand side platform. In FIG. 1, the overview blockdiagram 100 for a system according to the invention includes a DSP(demand-side platform) 114 that interacts with advertiser/clients 116;supply side partners 102; and sources 124 of third party viewershipdata. The demand-side platform 114 utilizes automation softwareoperating on one or more servers/processors 112 to bid for ad slots 104to be shown to viewers 108 via media property or TV programming 106.Online advertising and/or TV programming supply side partner(s) 102typically provide a sale opportunity or bid request package110—typically including ad slot data—to the demand-side platform 114.The demand-side platform will, in turn and if appropriate, provide aresponse 118 to supply side partner 102, that response including a bidand either an advertisement or information describing an advertisement.The decision to bid, and how much to bid, is automatically calculated bysoftware running on the one or more servers 112 where targeting andplanning information 120 supplied by advertiser/client 116 is processed.Such information may include for example and without limitation: desiredon-target impressions; campaign targeting parameters; campaign runtime;campaign budget; maximum bid; and TV campaign data and desired campaignstrategy. During the campaign planning stage, the DSP provides campaigncost estimates 122 and estimates for results to advertiser/clients 116.

FIG. 2 shows a flow chart describing a process for planning a crossformat campaign where an advertiser/client wishes to plan the campaignsuch that viewers who did not watch certain ads on TV get to see them ondigital media, thereby increasing the reach of the campaign—the processreferred to as optimization by de-duped reach. In step S202 a fused dataset of viewership data is received that includes both TV viewing anddigital media viewing of advertisements, and where for a plurality ofspecific viewers watching TV advertisements the data set includesdigital media viewership data for those specific viewers. In step S204,a list of proposed or historical TV advertisements is received for aparticular advertiser/client. In step S206, the fused data set isanalyzed for each respective TV advertisement to:

-   -   (i) identify those viewers in the fused data set who are        categorized as NOT WATCHING the TV advertisement;    -   (ii) identify viewer characteristics of the viewers categorized        as NOT WATCHING the TV advertisement; and    -   (iii) produce a list of MPs visited by the viewers in the fused        data set categorized as NOT WATCHING the TV advertisement, and        identify specific characteristics of those MPs;

In step S208, targeting criteria from an advertiser/client is receivedfor a future campaign. In step S210, a historical database containingdata from online advertising campaigns is analyzed, and based on thereceived targeting criteria for the future campaign and the data fromonline advertising campaigns, a model for the future campaign isproduced that includes a proposed budget split between TV and onlineplacement of advertisements.

FIG. 3 shows a flow chart describing a process for planning a crossformat campaign where an advertiser/client wishes to plan a campaignsuch that the viewing of certain ads on TV is reinforced by targetingthe same viewers on digital media in order to increase the frequency ofviewership of those ads—the process referred to as optimization byincreased frequency. In step S302, a fused data set of viewership datais received that includes both TV viewing and digital media viewing ofadvertisements, and where for a plurality of specific viewers watchingTV advertisements the data set includes digital media viewership datafor those specific viewers. In step S304, a list of proposed orhistorical TV advertisements is received for an advertiser/client. Instep 306, the fused data set is analyzed for each respective TVadvertisement to:

-   -   (i) identify those viewers in the fused data set who are        categorized as WATCHING the TV advertisement;    -   (ii) identify viewer characteristics of the viewers categorized        as WATCHING the TV advertisement; and    -   (iii) produce a list of MPs visited by the viewers in the fused        data set categorized as WATCHING the TV advertisement, and        identify specific characteristics of those MPs;

In step S308, targeting criteria is received from an advertiser/clientfor a future campaign. In step S310, a historical database containingdata from online advertising campaigns is analyzed, and based on thereceived targeting criteria for the future campaign and the data fromonline advertising campaigns, a model for the future campaign isproduced that includes a proposed budget split between TV and onlineplacement of advertisements.

FIG. 4 shows a flow chart describing a process for planning a crossformat campaign where an advertiser/client wishes to plan a campaignsuch that the lowest cost per impression is achieved without regard towhether or not a TV viewer sees the same ad on digital media—the processreferred to as optimization by “cheapest to reach”. In step 402, a fuseddata set of viewership data is received that includes both TV viewingand digital media viewing of advertisements, and where for a pluralityof specific viewers watching TV advertisements the data set includesdigital media viewership data for those specific viewers. In step 404, alist of proposed or historical TV advertisements is received for anadvertiser/client. In step 406, the fused data set is analyzed for eachrespective TV advertisement to:

-   -   (i) identify those viewers in the fused data set who are        categorized as WATCHING OR NOT WATCHING the TV advertisement;    -   (ii) identify viewer characteristics of the viewers categorized        as WATCHING OR NOT WATCHING the TV advertisement; and    -   (iii) produce a list of MPs visited by the viewer in the fused        data set categorized as WATCHING OR NOT WATCHING the TV        advertisement, and identify specific characteristics of those        MPs.

In step 408, targeting criteria is received from an advertiser/clientfor a future campaign. In step S410, a historical database containingdata from online advertising campaigns is analyzed, and based on thereceived targeting criteria for the future campaign and the data fromonline advertising campaigns, a model for the future campaign isproduced that includes a proposed budget split between TV and onlineplacement of advertisements.

For the processes of FIGS. 2, 3, and 4, the campaign model includestarget lists for both TV demographics and MPs targeted for digitalmedia. The lists are combined and sorted to produce an overall targetlist for a campaign. The combined list can be then sorted by costefficiency (cost per on-target impression) to produce a prioritizedtargeting list for the future campaign.

Note that TV viewership information used in the process may be relatedto past advertising campaigns for TV or may alternately be projected TVviewership information. Characteristics of MPs may include withoutlimitation one or more of demographic information; the cost ofpurchasing impressions on the MP; a historical “reach” for the MP whichreflects how frequently impression opportunities arise for that MP. Notethat ad campaigns usually have a specified run time, and if a particularMP has a very small reach it may contribute little value to a campaignif impression opportunities for that MP appear infrequently.

Optimization for a campaign targeting both TV and digital media can beperformed for cost and/or for reach, including optimization for CPMs(Cost per 1,000 on-target impressions) and/or GRPs (Gross RatingPoints).

A campaign planner at an advertiser/client needs the latest data to beincluded in a cross format planning tool so that they can be confidentin the results of the tool, by recognizing that the data from theirhistorical TV buy is correct. This is accomplished by:

-   -   building a historical record of the previous year's data    -   using the planning tool by month, quarter, or year    -   handling updates from a 3^(rd) party (e.g., Nielsen) when they        correct data    -   identifying when there are gaps in the datasets, indicating        where for some reason all the data is not available    -   acquiring datasets from a 3^(rd) party that tracks viewership        equivalent to the following datasets available from Nielsen:        -   National People Meter;        -   Netview & VideoCensus;        -   Fusion; and        -   Monitor Plus

Note that 3^(rd) party viewership data suppliers may supply dataindicative of a viewer panel and/or actual viewership data acquired bymonitoring a large number of viewers over time. The most prominentsupplier of viewership data today in the United States is Nielsen,however other sources of viewership data exist, and without limitationsuch other sources may include for example Barb in the UK, OZTam inAustralia, and Rentrak in the US. The embodiments described herein donot rely on any specific supplier of viewership data, and any specificmention of data packages supplied by, for example Nielsen, are onlyexemplary.

FIG. 5 shows a matrix defining different data sets used for cross formatadvertising campaign planning. Four data sets 502-508 of the five totaldata sets are examples of those available from third-party viewershipdata suppliers such as, for example, Nielsen. As shown in FIG. 5, theNational People Meter 502 shows minute by minute TV viewing and whensupplied by Nielsen contains for example 55,000 respondents—the majorityof whom have Internet access and recording devices for Internetactivity. The data set entitled NetView & VideoCensus 504 when suppliedby Nielsen contains for example 200,000 respondents with Internetactivity tracking. The Fusion data set 506 contains approximately255,000 respondents where TV and Internet usage is fused andextrapolated. The data set entitled Monitor plus 508, when supplied byNielsen, shows TV activity with related cost data. Data set 510,supplied by a demand-side platform, provides Internet site (MP) data andrelated advertising data. For each supplied data set, descriptions forContents 512, Sample Size 514, and Key Elements for the Planner 516 areshown.

FIG. 6 shows how the various data sets of FIG. 5 are linked and analyzedin creating a cross format advertising campaign. Note in particular forlinkage number “3” 602 that demographic characteristics of those viewerstracked for Internet and TV usage are linked to TV and online video addata. For linkage number “4” 604 in FIG. 6, sites (MPs) visited byviewers who saw particular TV ads are linked with sites they did NOTvisit. This linkage is required for de-duped (un-duplicated) reach.Sites (MPs) unseen by those who saw a TV ad can be used by the DSP togenerate a cross format campaign for incremental reach as describedherein.

FIG. 7 shows one exemplary user interface for the planning stage 702 ofa cross format campaign, where an advertiser/client's current plan 704for TV advertising is analyzed 706 to provide a baseline. The audience708 for the plan is entered, including Gender 710, which can be Male,Female or All genders. The targeted age bracket 712 for the TV plan isentered by independently positioning slider nodes 716 and 718 onhorizontal age bracketing tool 714 to visually bracket the targetedages. A functionality of the user interface of FIG. 7 includes ahistogram graph showing a viewer population distribution 720 thatappears under horizontal age bracketing tool 714, and can be optionallytruncated at either or both ends as either or both of slider nodes 716and 718 are moved to indicate the age distribution within thespecifically bracketed ages. Also, as either or both of slider nodes 716and 718 are moved, the targeted (bracketed) population 712 isautomatically updated. At the bottom left, a Discount from Rack Rate 722can be entered. Timeframe 724 to be analyzed for the plan is entered anda summary of results 726 is automatically presented to the planner. Theexemplary and non-limiting summary of FIG. 7, includes: Reach; Reach(%); gross impressions; GRPs; average frequency; total cost; eCPM; andeCPP.

FIG. 8 shows an exemplary user interface for the planning stage of across format campaign where a planner on behalf of a client advertisermay observe the effect of shifting portions of their TV advertisingbudget to digital media, in this figure referred to as online video adsor (OLV). Here, in the box 802 at the upper left, the planner Optimizesby Target by choosing from three basic strategies for the cross formatcampaign that can be automatically calculated according to the inventionbased on the data sets supplied:

-   -   (i) “Are the cheapest to reach”—where the campaign combines TV        and digital media without concern for whether or not digital        media viewers in the fused data set saw or did not see ads on        TV;    -   (ii) “Didn't see my ad on TV”—where the strategy is focused on        de-duplication in order to increase the reach of the combined        campaign; and    -   (iii) “Saw my ad on TV”—where the strategy is focused on        reinforcing TV viewership with online impressions in order to        increase the frequency of the combined campaign.

Alternately, a planner can manually optimize the campaign bymanipulating a slider bar 804 located at the left side of the displayshown in FIG. 8. The position of the bar affects both the reach and costof the campaign, and as the slider bar is manipulated the resultantparameters shown on the right side of the screen in FIG. 8 areautomatically calculated and change accordingly to display thecalculated parameters. As slider bar 804 is moved horizontally, a choiceis automatically made for reach 808 with respect to proportions of OLV810 versus TV Only 812. Also with respect to impressions, a choice forCPM 814 is automatically made with respect to a percentage shift towardsOLV.

On the right-hand side of the user interface display of FIG. 8,parameters 816 guide the plan for this advertising placement that wasset in other screens are shown and include the brand; the demographicage/gender parameters; and the timeframe. As key parameters on the lefthand side of FIG. 8 with respect to shifting between TV and OLV arechanged by a planner utilizing this user interface, results areautomatically updated by underlying processes according to embodimentsof the invention. For instance, a new percentage for unduplicated reach818 is displayed as well as a change in average frequency 820. Estimatednumbers of impressions 822 are updated along with financial savings 824resulting from the plan. Finally, at the bottom right of FIG. 8 is asummary 826 for the plan, including parameters 726 that were shown withrespect to FIG. 7. For FIG. 8 however, these projected results are shownseparately with respect to a TV Schedule 828; and Online Video AdSchedule 830; and a Combined Schedule 832.

FIG. 9 shows an alternative functionality for guiding the split betweenTV ad spending and digital media ad spending. Similar to FIG. 8, butwith a different graphical appearance, choices for automaticoptimization by target 802 is shown in the upper left corner of the userinterface display of FIG. 9. Similar to FIG. 8, the basic strategy ischosen by the planner to be one of “cheapest to reach”; “did not see myTV ad”; and “did see my TV ad”. Below targeting choice 802, a radialdial mechanism for budget adjustment 902 is presented at the leftwhereby the planner can choose the percentages for the split between TVand Online Video. A unique fan shaped graphical input mechanism 906 ispresented to the planner where by dragging node 904 left or right aroundthe arc of fan 906, a budget shift can be defined between TV and OnlineVideo. Alternately, a shift percentage 908 may be entered, or a dollaramount 910 can be entered to define the shift.

As fan dial 906 is rotated, resultant projected parameters areautomatically calculated and displayed at the right along with exampleonline placements. At the top right of the display, prominent boxes areshown with parameter changes to help guide the planner including: a NewIncremental Reach 912; a Change in Frequency 914; a Change inImpressions 916; and Per CPM Savings 918. At the center-right of thedisplay is a graph 920 showing a percentage reached of the populationwith respect to the percentage split between OLV and TV. Specific graphsfor TV-Only 922, OLV+TV 924, and OLV-Only 926 are shown along with anoverall CPM savings 928.

At the bottom of the user interface display of FIG. 9 is a resultsummary 930, which is similar to summary 826 of FIG. 8, and also asummary 932 of online placements characterized by viewer interestarea—including for example and without limitation: men's lifestyle;sports; automotive; and fitness. Included for each of these viewerinterest areas is either a projected cost as shown in the displayexample, or alternately projected impressions. Which of cost orimpressions are shown for the placement breakdown at the lower right ofFIG. 9 is controlled by selector 934.

FIG. 10 shows the user interface for a planning tool which allowsplanners to adjust their campaign and observe automatically projectedresults in terms of on-target impressions, GRPs, and cost. This tool waspreviously shown and described in co-pending U.S. Patent ApplicationPublication No. 2014-0278912 entitled: “Systems and Methods forPredicting and Pricing of Gross Rating Point scores by Modeling ViewerData”. When used in conjunction with cross format planning tools such asthose shown in FIGS. 7, 8, and 9, the user interface shown in FIG. 10now incorporates data and planning for a cross format campaign targetingboth TV advertising and digital media advertising.

At the top of the exemplary user interface display of FIG. 10 is aninformation bar 1002 that contains: the name of the placement; amechanism for choosing the campaign and editing options; the particularplanner's email address; and a search tool. At the top left side areselectors for planning according to CPM 1004 or GRP 1006. Under theseselectors is an audience targeting mechanism similar to that previouslyshown in FIG. 7, and includes selection 702 for age and gender, and inparticular includes horizontal selector bar 718 with individuallypositioned slider nodes 716 and 718 that are manipulated by the plannerto bracket the lower and upper bounds respectively of the targeted agebracket. As with FIG. 7, a graphical histogram 720 of the agedistribution bracketed by selector bar 718 is also shown. Placementparameters are entered here such as for example and without limitation aGRP goal 1008 that may be entered as well as a Frequency Cap 1010. Atthe bottom left of the user interface display of FIG. 10 are additionalplacement parameters such as budgeting controls 1012, including dates1014 and a budget 1018. A planner may further select particular daypartsto address by clicking the daypart selector 1016 which brings up a userinterface facility for daypart selection. An inventory tier 1020 to beutilized is chosen at the bottom left. A planner may choose one or moreclassifications or segmentations of MPs to be addressed by a campaign,herein labeled “Inventory Tiers” 1020. For this non-limiting example,available classifications include tiers ranging from MPs that are verywell-recognized to those that are less recognizable. For example, Tier 1can represent sites a user's friends and family would recognize. Tier 2can represent MPs with lower brand recognition or awareness. Tier 3 canrepresent brand-safe sites that are niche or reach. “Brand safe” refersto MPs where there is nothing controversial such as guns, sex, violence,or alcohol, etc. “Niche” means there is a smaller audience, such as forinstance a site for vegan cooks. “Reach” sites are MPs with hugeaudiences and many demographics such as YouTube, CBS, etc. Reach sitesprovide broad exposure, however with little specific brand alignment.

On the right-hand side of the user interface display of FIG. 10 areforecasted results including at the top projected CPP 1022; projected OnTarget CPM and % 1024; and a GRP Goal and Expected value 1026. Amechanism is also included to Revert Changes 1028. A graph 1030 ofprojected GRP results is shown with respect to budget, and anannunciator 1032 is shown positioned on the graph in response to a valueentered as budget 1018. Projected total impressions 1034 are shown atthe bottom right along with projected total GRPs 1036 and projectedUniques 1038.

FIG. 11 shows a planning tool for a cross format platform focused on GRPor CPM results and including advanced/strategic targeting choices thatgo beyond simple age and gender to include viewer characteristics suchas for example and without limitation: income; marital status;education; presence of children; homeownership; and ethnicity. Alsoincluded are exemplary choices for advanced targeting of buyerbehavior—which could be either modeled or actual behavior—in thisinstance targeting a specific product or service that a shopper mightbuy and also targeting a frequency for their purchase of that product orservice. Also included are choices of different target screen formatsfor display platforms including platform variations for both TV anddigital media, ensuring that planners using the tool per FIG. 11 havethe ability to optimize for de-duplication or reach across all formatsand screen types.

At the top of FIG. 11, a facility 1102 for loading previous media plansis provided and includes a date range 1104 and a timeframe specification1106 that provides for specification of quarters or a full year. Belowthat, a facility for budget entry 1108 is provided for planning a newcampaign with a specified date range 1110 and budget 1112. Next,campaign goals are specified that include advanced/strategic targeting1114; age bracket targeting 1128; and shopper targeting 1130.Advanced/strategic targeting 1114 includes targeting for: income 1116;marital status 1118; education 1120; presence of children 1122; homeownership 1124; and ethnicity 1126. Age bracket targeting 1128 utilizesa horizontal age bracketing tool 714 as previously shown in FIG. 7, withindependently positioned slider nodes 716 and 718 to visually bracketthe targeted ages. Age bracketing tool 714 is linked with histogramgraph 720 showing a viewer population distribution that appears underhorizontal age bracketing tool 714, and can be optionally truncated ateither or both ends as either or both of slider nodes 716 and 718 aremoved. Shopper targeting 1130 shows for this example targeting shopperswho buy toothpaste 1132, however this is exemplary and drop-down arrowsallow editing to target a wide variety of products and services.Frequency 1134 for a viewer's purchase of a product or service can alsobe targeted. At the bottom of the user interface display of FIG. 11 isthe ability to select different cross screen formats 1136 for targeting.An exemplary list of screen types shown for targeting includes withoutlimitation: TV; Addressable TV; Online video; VOD; Mobile; Tablet; andNetwork extension.

FIG. 12 shows an exemplary user interface for an additional planningtool for a cross format campaign, where a planner may view/edit 1202 aplan. An editable strategy summary 1204 is shown in the upper left,including date range 1206, budget 1208, and targeting criteria similarto those shown in FIG. 11, including gender targeting 1210 and agebracket targeting 1128, plus advanced/strategic targeting including forexample and without limitation: income 1214; marital status 1216;education 1218; presence of children 1220; home ownership 1222; andethnicity 1224.

At the top right of the user interface display of FIG. 12 is a graph1238 showing % Reach with respect to Budget, and with the results brokendown with separate subgraphs for different display platform typesincluding: TV; online; mobile; and VOD. The Incremental Reach fromDigital 1242 has been automatically calculated and is specifically shownat the point on the graph corresponding to the specified budget amount.An annunciator balloon 1240 is shown aligned with the specified budgetnumber on the horizontal axis of the graph, and includes withinannunciator balloon 1240 a display of the specified budget number andthe average CPM.

A prioritized list of placement targets 1226 is shown at the lower leftthat resulted from the process shown in FIG. 2 for a campaign where theoverriding strategy is incremental reach via non-duplication between TVand digital media. Here a “Combined” list 1228 is shown, however thelist can be shown specifically focused on any of the following formatsby selecting the appropriate tab: TV; Addressable TV; Online video; VOD;Mobile; Tablet; and Network extension. The displayed placement list 1228can be sorted by spend or sorted by format 1236. Network names aredisplayed 1230 with logo and editable checkboxes forinclusion/exclusion. Horizontal bar graphs 1232 are included to visuallyindicate relative spending, and forecasted dollar spend 1234 isadditionally shown. At the bottom center of the user interface display,a graph 1244 of relative media format mix is shown with horizontal barsfor each format type including a percentage for each format as well asCPMs and CPPs. To the right of the media mix graph 1244 are prominentboxes indicating average CPM 1246 and average CPP 1248.

FIG. 13 shows an additional planning tool for a cross format campaign.Here, the results are shown in terms of CPP (cost per GRP point) andcost for on target impressions. Also shown are prioritized lists ofplacement targets, where a different prioritized list has beenestablished for each of a plurality of display platform types. At theupper left of the user interface screen of FIG. 13 is a strategy summaryfor a cross format plan that was previously shown as part of the userinterface of FIG. 11. Date range 1110 and budget 1112 are shown alongwith a targeting summary 1114 including conventional age/genderdemographic targeting as well as advanced/strategic targeting for:income; marital status; education; presence of children; homeownership;and ethnicity. At the top right of the user interface display of FIG. 13is a graph 1316 showing GRPs versus budget with a specified budget 1320indicated by a horizontal dotted line, and annunciator balloon 1318shown vertically above the specified budget location on the horizontalaxis, where the annunciator balloon additionally indicates the budgetnumber. At the right of graph 1316 are prominent boxes displaying: CPP1322; On target CPM and % 1324; and GRPs 1326.

At the bottom of the user-interface display of FIG. 13 is a placementsummary 1304 similar to summary 1226 of FIG. 12, however here the tabfor Mobile 1302 has been selected, and therefore placements 1304 shownbelow indicate placement specifically planned for viewing on mobiledevices. For each entry, a logo 1306 is typically displayed next to anetwork name, and for networks where reservations are appropriate orrequired for placement a button marked “Reserve” 1312 is shown. Notethat some network categories such as 1308 have subnetworks 1310 whereplacements may be individually planned, and an arrow icon at the left ofthe network name allows expansion below to reveal available subnetworks1310, in this example ESPN.com and FOXSports.com. Most of the parametersshown on the user interface of FIG. 13 that guide placements for anadvertising campaign are editable, and in addition to editing individualfields, sites can be added to the placement list by selecting button1314.

FIG. 14 shows an additional tool for reviewing a cross format campaignprior to execution 1402, includes target placements for both TV anddigital media, and including campaign start and end dates, and projectedcosts. A button 1440 is provided to move from this tool to a tool asshown for example in FIG. 10 from where a final view of the projectedcampaign can be examined followed by executing the campaign. At the topof the exemplary user-interface display of FIG. 14 is a TV ReservationList 1404, displaying a summary of networks that have been added to thereservation list where reservations are appropriate or required forplacement on a particular network. At the left of Reservation List 1404,placement names are shown 1408, including projected GRPs, network name,and an annunciator icon that includes the particular type of placement,such as TV or OLV. Date ranges 1410 are shown for each placement alongwith network name and logo 1412. Also shown for each reserved placementare: projected CPM 1414; projected impressions 1416; and status 1418.For each reserved placement, a tool icon 1420 is shown that allows theplanner to observe and edit options for the particular reservedplacement. Also, for each reserved placement a “Send” button 1422 isprovided to send the request for placement reservation as well as amaster button 1424 that enables the planner to send all reservationrequests at once.

The bottom of the exemplary user-interface display of FIG. 14 is asummary of Online Placements 1406. Here, for each placement, thePlacement name is shown along with: Date ranges 1434; projected CPMs1436; Impressions 1438; and projected Cost 1442. When a planner wishesto see more detail for a given placement such as network and daypartinformation 1432, an arrow annunciator icon such as that shown for theSports category 1426 can be clicked, displaying additional detail onspecific network placements falling within the selected (Sports)category. In this example, there are two sub-placements within theSports placement category: ESPN.com shown as a Mobile placement 1428 andFOXSports.com shown as an Online placement 1430. Note that Daypartinformation 1432 is then viewable for both the ESPN and FOXSportsplacements.

The processes performed as described herein are implemented as engines(sequential machines) running on one more processors, wherein theengines:

-   -   receive input from a user/planner through a realtime user        interface;    -   access various databases;    -   compute estimated campaign results in realtime;    -   report those estimated results to the user/planner through the        realtime user interface;    -   enable and control the execution of the advertising campaign;        and    -   report to the user/planner the results of the actual advertising        campaign.

Note that the quantity and complexity of the data and tasks involved inoperating the invention make implementation of the invention impossiblewithout the aid of one or more sequential machines—typically sequentialprocesses operating on the one or more processors referred to above—andalso use of a hardware communications infrastructure—typically theInternet. During the analysis and actionable processes involved,millions of data elements must be considered and without using a machineas part of the invention, implementation of the claimed processes wouldnot be possible. Typically a Demand Side Platform (DSP) MUST bothanalyze and respond to an ad slot opportunity in less than 100milliseconds. Performing the claimed processes with “pencil and paper”is impossible for many reasons, as is performing the process without theInternet. In fact, the entire process with respect to onlineadvertisements requires an intimate usage of the Internet for the DemandSide Platform to communicate with: supply-side platforms; advertisingexchanges; advertising networks; and attribution partners. The DSP mustreceive bid request packages, place bids, and supply the ads themselvesin milliseconds via the Internet. Then, after a campaign has run, theDSP automatically receives attribution data from attribution partners.The preceding description names only some of the automated processes andactions involved in implementing the invention as claimed.

The claims reflect a computerized process since, at this time, computingresources have evolved to include “Cloud-based” computing as describedabove in the Background section. As such, it is also impossible topredict where (physically) the claimed processes will be executed and/orif they will be distributed across multiple machines. It is alsoimpossible to predict the specific ownership of machines whereupon theclaimed processes will be executed, and therefore against whom theclaims would protect against should the claims instead have been writtenas system claims as opposed to the method claims attached hereto.

The foregoing detailed description has set forth a few of the many formsthat the invention can take. It is intended that the foregoing detaileddescription be understood as an illustration of selected forms that theinvention can take and not as a limitation to the definition of theinvention. It is only the claims, including all equivalents that areintended to define the scope of this invention.

At least certain principles of the invention can be implemented ashardware, firmware, software or any combination thereof. Moreover, thesoftware is preferably implemented as an application program tangiblyembodied on a program storage unit, a non-transitory machine readablemedium, or a non-transitory machine-readable storage medium that can bein a form of a digital circuit, an analog circuit, a magnetic medium, orcombination thereof. The application program may be uploaded to, andexecuted by one or more machines comprising any suitable architecture.The various processes and functions described herein may be either partof microinstruction code or part of one or more application programs, orany combination thereof, which may be executed by one or more CPUs,whether or not such machine(s) or processor(s) are explicitly shown. Inaddition, various other peripheral units may be connected to machineplatforms such as one or more data storage units and printing units.

What is claimed is:
 1. A computerized method for planning an advertising campaign targeting both TV and online impressions, whereby one or more processors perform the computerized method, comprising: receiving a fused data set of viewership data that includes TV viewing and digital media viewing of advertisements, and where for a plurality of viewers watching TV advertisements the fused data set includes digital media viewership data for those viewers; receiving a list of TV advertisements for an advertiser/client; analyzing the fused data set to: for each of the listed TV advertisements, identify those viewers in the fused data set who are categorized as not watching the respective listed TV advertisement; identify viewer characteristics of the viewers categorized as not watching the respective listed TV advertisement, and produce a list of MPs visited by the viewers in the fused data set categorized as not watching the respective listed TV advertisement, and identify specific characteristics of those MPs; receiving targeting criteria from the advertiser/client for a future campaign; and analyzing a historical database containing data from digital media advertising campaigns, and based on the received targeting criteria for the future campaign and the data from digital media advertising campaigns, producing a model for the future campaign that includes a proposed budget split between TV and digital media placement of advertisements.
 2. The computerized method of claim 1 wherein the categorization of viewers not watching the listed TV advertisements includes viewers who did not watch the listed TV advertisements in the past.
 3. The computerized method of claim 1 wherein the categorization of viewers not watching the listed TV advertisements includes one or both of viewers who did not watch the listed TV advertisements in the past or viewers who are projected to not watch the listed TV advertisements in the future.
 4. The computerized method of claim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least demographic characteristics.
 5. The computerized method of claim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least characteristics related to cost of purchasing impressions on each MP.
 6. The computerized method of claim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least reach characteristics.
 7. The computerized method of claim 1 wherein the model for the future campaign is optimized for at least one of cost or reach.
 8. The computerized method of claim 1 further comprising generating a target list of MPs visited by the viewers in the fused data set categorized as not watching the listed TV advertisements, and that are described in the historical database with respect to: a demographic profile of each MP; a historical cost of purchasing impressions on each MP; or a historical reach of each MP.
 9. The computerized method of claim 8 further comprising generating a combined target list for the future campaign by: creating a combined list of TV demographic targets combined with the target list of MPs; and sorting the combined list with respect to cost efficiency for on-target impressions.
 10. The computerized method of claim 9 further comprising executing the future campaign by initially targeting advertising opportunities in the combined list that have a lowest cost for on-target impressions.
 11. A computerized method for planning an advertising campaign targeting both TV and online impressions, whereby one or more processors perform the computerized method comprising: receiving a fused data set of viewership data that includes TV viewing and digital media viewing of advertisements, and where for a plurality of viewers watching TV advertisements the fused data set includes digital media viewership data for those viewers; receiving a list of TV advertisements for an advertiser/client; analyzing the fused data set to: for each of the listed TV advertisements, identify those viewers in the fused data set who are categorized as watching the respective listed TV advertisement; identify viewer characteristics of the viewers categorized as watching the respective listed TV advertisement, and produce a list of MPs visited by the viewers in the fused data set categorized as watching the respective listed TV advertisement, and identify specific characteristics of those MPs; receiving targeting criteria from the advertiser/client for a future campaign; and analyzing a historical database containing data from digital media advertising campaigns, and based on the received targeting criteria for the future campaign and the data from digital media advertising campaigns, producing a model for the future campaign that includes a proposed budget split between TV and digital media placement of advertisements.
 12. The computerized method of claim 11 wherein the categorization of viewers watching the listed TV advertisements includes viewers who watched the listed TV advertisements in the past.
 13. The computerized method of claim 11 wherein the categorization of viewers watching the listed TV advertisements includes one or both of viewers who watched the listed TV advertisements in the past and viewers who are projected to watch the listed TV advertisements in the future.
 14. The computerized method of claim 11 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements include at least demographic characteristics.
 15. The computerized method of claim 11 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements include at least characteristics related to cost of purchasing impressions on each MP.
 16. The computerized method of claim 11 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements include at least reach characteristics.
 17. The computerized method of claim 11 wherein the model for the future campaign is optimized for at least one of cost and reach.
 18. The computerized method of claim 11 further comprising generating a target list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements, and that are described in the historical database with respect to: a demographic profile of each MP; a historical cost of purchasing impressions on each MP; or a historical reach of each MP.
 19. The computerized method of claim 18 further comprising generating a combined target list for the future campaign by: creating a combined list of TV demographic targets combined with the target list of MPs; and sorting the combined list with respect to cost efficiency for on-target impressions.
 20. The computerized method of claim 19 further comprising executing the future campaign by initially targeting advertising opportunities in the combined list that have a lowest cost for on-target impressions.
 21. A computerized method for planning an advertising campaign targeting both TV and online impressions, whereby one or more processors perform the computerized method comprising: receiving a fused data set of viewership data that includes TV viewing and digital media viewing of advertisements, and where for a plurality of viewers watching TV advertisements the fused data set includes digital media viewership data for those viewers; receiving a list of TV advertisements for an advertiser/client; analyzing the fused data set to: for each of the listed TV advertisements, identify those viewers in the fused data set who are categorized as watching or not watching the respective listed TV advertisement; identify viewer characteristics of the viewers categorized as watching or not watching the respective listed TV advertisement, and produce a list of MPs visited by the viewers in the fused data set categorized as watching or not watching the respective listed TV advertisement, and identify specific characteristics of those MPs; receiving targeting criteria from the advertiser/client for a future campaign; and analyzing a historical database containing data from digital media advertising campaigns, and based on the received targeting criteria for the future campaign and the data from digital media advertising campaigns, producing a model for the future campaign that includes a proposed budget split between TV and digital media placement of advertisements.
 22. The computerized method of claim 21 wherein the categorization of viewers watching or not watching the listed TV advertisements includes viewers who watched or did not watch the listed TV advertisements in the past.
 23. The computerized method of claim 21 wherein the categorization of viewers watching the listed TV advertisements includes one or both of viewers who watched or did not watch the listed TV advertisements in the past and viewers who are projected to watch or not watch the listed TV advertisements in the future.
 24. The computerized method of claim 21 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set include at least demographic characteristics.
 25. The computerized method of claim 21 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set include at least characteristics related to cost of purchasing impressions on each MP.
 26. The computerized method of claim 21 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set include at least reach characteristics.
 27. The computerized method of claim 21 wherein the model for the future campaign is optimized for at least one of cost and reach.
 28. The computerized method of claim 21 further comprising generating a target list of MPs visited by the viewers in the fused data set categorized as watching or not watching the listed TV advertisements, and that are described in the historical database with respect to: a demographic profile of each MP; a historical cost of purchasing impressions on each MP; and a historical reach of each MP.
 29. The computerized method of claim 28 further comprising generating a combined target list for the future campaign by a computerized method further comprising: creating a combined list of TV demographic targets combined with the target list of MPs; and sorting the combined list with respect to cost efficiency for on-target impressions.
 30. The computerized method of claim 29 further comprising executing the future campaign by initially targeting advertising opportunities in the combined list that have a lowest cost for on-target impressions. 